Genome-wide association studies (GWAS) are an effective and increasingly affordable tool to investigate genetic contributions to human health. However, existing data are limited by homogeneity of samples, modest environmental data, and absence of longitudinal information. These limitations preclude a dynamic, multilevel integrative approach to health that captures bidirectional biological and contextual contributions and their interactions over time. To address this gap, this application proposes to complete genotyping on approximately 6,000 archived DNA samples using whole genome array technology, and make available to the global scientific community an unprecedented national resource of rich, longitudinal environmental data coupled with comprehensive phenotype and genotype data on more than 12,000 participants in the nationally representative, ethnically diverse Add Health sample. Add Health has archived DNA specimens for future research and is currently genotyping approximately 6,000 samples for GWAS. This project will complete genotyping on the entire sample, disseminate these data and conduct preliminary GWAS. We have three specific aims: Aim 1) Using the Illumina Omni1-Quad BeadChip (more than 1 million genetic markers), complete genotyping on the archived DNA, yielding a sample of 12,000. Aim 2) Develop a national and global resource for the scientific community by collaborating with dbGaP to deposit Add Health genotype, phenotype, and environmental data. Aim 3) Conduct preliminary GWAS and explore gene x environment (GxE) interactions to identify biological and contextual contributions to phenotypes that are well-defined in Add Health and with which the investigative team has substantive expertise, including obesity, substance use, and cardiovascular disease. Add Health sampled the multiple environments in which young people live their lives, including the family, peers, school, neighborhood, community, and relationship dyads, and provides independent and direct measurement of these environments over time. Add Health contains extensive longitudinal information on health-related behavior, including life histories of physical activity, involvement in risk behavior, substance use, sexual behavior, civic engagement, education, and multiple indicators of health status based on self-report (e.g., general health, chronic illness), direct measurement (e.g., overweight status and obesity), and biomarkers (e.g., blood spots). No other data resource with this expanse of genotype and phenotype data on a large nationally representative longitudinal sample with race, ethnic, socioeconomic, and geographic diversity exists.